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Signal Processing Noise by Vyacheslav Tuzlukov - 9780849310256
Signal Processing Noise by Vyacheslav Tuzlukov - 9780849310256

Signal Processing Noise by Vyacheslav Tuzlukov - 9780849310256

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Signal Processing NoiseAuthor(s): Vyacheslav Tuzlukov\nFormat: Hardback\nPublisher: Taylor & Francis Inc, United States\nImprint: CRC Press Inc\nISBN-13: 9780849310256, 978-0849310256\nSynopsis\nAdditive and multiplicative noise in the information signal can significantly limit the potential of complex signal processing systems, especially when those systems use signals with complex phase structure. During the last few years this problem has been the focus of much research, and its solution could lead to profound improvements in applications of complex signals and coherent signal processing.\n\nSignal Processing Noise sets forth a generalized approach to signal processing in multiplicative and additive noise that represents a remarkable advance in signal processing and detection theory. This approach extends the boundaries of the noise immunity set by classical and modern signal processing theories, and systems constructed on this basis achieve better detection performance than t.

Signal Processing Noise by Vyacheslav Tuzlukov - 9780849310256

Signal Processing NoiseAuthor(s): Vyacheslav Tuzlukov\nFormat: Hardback\nPublisher: Taylor & Francis Inc, United States\nImprint: CRC Press Inc\nISBN-13: 9780849310256, 978-0849310256\nSynopsis\nAdditive and multiplicative noise in the information signal can significantly limit the potential of complex signal processing systems, especially when those systems use signals with complex phase structure. During the last few years this problem has been the focus of much research, and its solution could lead to profound improvements in applications of complex signals and coherent signal processing.\n\nSignal Processing Noise sets forth a generalized approach to signal processing in multiplicative and additive noise that represents a remarkable advance in signal processing and detection theory. This approach extends the boundaries of the noise immunity set by classical and modern signal processing theories, and systems constructed on this basis achieve better detection performance than t.

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